1. Open RStudio and create an RMarkdown (.Rmd) file. Click File > New File > R Markdown Choose Document > HTML output

R Markdown

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

summary(cars)
##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00

Including Plots

You can also embed plots, for example:

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.

Always the First thing - Set working directory

# Change to your directory
setwd("/Users/yuchen/Desktop/Scripts")

NOW, let’s do some fun stuff

  1. Drawing in R

install the package we need

Different ways of installing package - TurtleGraphics

install.packages(“TurtleGraphics”)

# load the package by calling the library() function:
library("TurtleGraphics")
## Loading required package: grid
#creates a plot region and places the Turtle in the center, facing up
turtle_init()

turtle_forward(dist=30)

1.1 Let’s think how can we draw a triangle

turtle_init()

turtle_forward(dist=30)

turtle_left(angle=120)

turtle_forward(dist=30)

turtle_left(angle=120)

turtle_forward(dist=30)

Now let’s try to draw an square or even a star!

1.2 for loops - easier to do the repeat things

turtle_init()

for (i in 1:3) {  # Loop runs 3 times to complete the square
  turtle_forward(dist=30)  # Move forward
  turtle_left(angle=120)     # Turn left
}

1.3 Define a function

turtle_star <- function(r) {
  for (i in 1:5){
    turtle_forward(dist=r)  # Move forward
    turtle_left(angle=144)     # Turn left
  }
}

1.4 How to call this function

turtle_init()

turtle_star(50)

1.5 Condition for loops

turtle_init()

turtle_do({
  for (i in 1:5) {
    x <- rnorm(1) #Generate a random number
    print(x)
    if (x > 0){
      turtle_forward(dist=5)
      turtle_star(30)  # call the turtle_star function
      turtle_left(angle=45)     # Turn left
    } else {
      turtle_forward(dist=10)
      turtle_star(20)  # Move forward
      turtle_right(angle=120)
    }
  }
})

## [1] -0.263916
## [1] 0.6185398
## [1] 0.1731611
## [1] 1.515412
## [1] 1.636187

2. R - Data structures:

•   Vectors: A sequence of elements of the same type.

•   Lists: A collection of different types of elements.

•   Data Frames: A table-like structure, similar to a spreadsheet.

•   Factors: A categorical data type.

2.1 Create and manipulate vectors

# Create a numeric vector
numbers <- c(10, 20, 30, 40, 50)
print(numbers)
## [1] 10 20 30 40 50
# Create a character vector
names <- c("Alice", "Bob", "Charlie")
print(names)
## [1] "Alice"   "Bob"     "Charlie"
# Access elements
numbers[2]  # Get the second element
## [1] 20
numbers[1:3]  # Get first three elements
## [1] 10 20 30

Key Points:

✅ Vectors hold elements of the same type (numeric, character, etc.).

✅ Use indexing ([]) to access elements.

2.2 Store different types of data in a list.

# Create a list with different types of elements
person <- list(name = "Alice", age = 25, scores = c(85, 90, 95))
print(person)
## $name
## [1] "Alice"
## 
## $age
## [1] 25
## 
## $scores
## [1] 85 90 95
# Access elements using `$` or `[[]]`
print(person$name)  # "Alice"
## [1] "Alice"
print(person[["age"]])  # 25
## [1] 25
print(person$scores[2])  # 90
## [1] 90

Key Points:

✅ Lists can contain different types of data.

✅ Access elements using $ or [[]].

2.3 tabular data (Most of our data will in this format)

# Create a data frame
students <- data.frame(
  Name = c("Alice", "Bob", "Charlie"),
  Age = c(25, 22, 23),
  Score = c(90, 85, 88)
)

# View data
print(students)
##      Name Age Score
## 1   Alice  25    90
## 2     Bob  22    85
## 3 Charlie  23    88
# Access a column
students$Age
## [1] 25 22 23
# Access a row
students[1, ]  # First row
##    Name Age Score
## 1 Alice  25    90
# Access a specific value
students[2, "Score"]  # Bob's score
## [1] 85

Key Points:

✅ Data frames store tabular data.

✅ Use $ to access columns, [row, col] for specific values.

2.4 categorical data

# Create a factor
genders <- factor(c("Male", "Female", "Male", "Female"))
print(genders)
## [1] Male   Female Male   Female
## Levels: Female Male
# Check factor levels
levels(genders)
## [1] "Female" "Male"
# Convert a character vector into a factor
education <- factor(c("High School", "Bachelor", "Master", "PhD"))
print(education)
## [1] High School Bachelor    Master      PhD        
## Levels: Bachelor High School Master PhD

Key Points:

✅ Factors represent categorical data (e.g., gender, education levels).

✅ Use factor() to create factors.

# Load TurtleGraphics package
library(TurtleGraphics)

# Initialize TurtleGraphics
turtle_init()

turtle_setpos(x=30, y=50)

turtle_do({
  for(i in 1:180) {
    turtle_forward(dist=1)
    turtle_right(angle=2)
    }
})

turtle_setpos(x=37, y=60)

turtle_lwd(lwd=3)
turtle_col(col="purple")
turtle_do({
  for(i in 1:90) {
    turtle_forward(dist=0.25)
    turtle_right(angle=2)
    }
})

turtle_setpos(x=65, y=60)

turtle_right(angle=180)

turtle_do({
  for(i in 1:90) {
    turtle_forward(dist=0.25)
    turtle_right(angle=2)
    }
})

turtle_setpos(x=42, y=45)

turtle_col(col="yellow")
turtle_lwd(lwd=8)
turtle_do({
  for(i in 1:90) {
    turtle_forward(dist=0.6)
    turtle_left(angle=2)
    }
})

# Hide the turtle at the end
turtle_hide()

More fun function can be found at : https://cran.r-project.org/web/packages/TurtleGraphics/vignettes/TurtleGraphics.pdf